Data Scientist
Location: GB, LND, Farringdon
Department: Engineering:Software Engineering
Employment type: Full-time
Required education: Bachelor's Degree
Industry: Computer Software
Function: Engineering

Company profile:
We build software for fashion retailers, to help them make the right commercial decisions about what to sell, and how to price it. Fashion is the 4th biggest industry in the world, so this is actually a huge problem economically, as well as environmentally for everyone in the world. The Guardian called us one of the 20 hottest London startups, and we're a quickly growing team, with a product used by some of the best retailers in the world, and we're backed by the smartest investors in Europe, the same ones who backed Etsy, Dropbox, ASOS and Net-a-Porter.

Job description:
About EDITDWe build software for fashion retailers, to help them make the right commercial decisions about what to sell, and how to price it. Fashion is the 4th biggest industry in the world, so this is actually a huge problem economically, as well as environmentally for everyone in the world. Both Mashable and The Guardian called us one of the 20 hottest London startups, and we're a quickly growing team, with a product used by some of the best retailers in the world, and we're backed by the smartest investors in Europe, including Index Ventures, who backed Etsy, Dropbox, ASOS and Net-a-Porter.The teamWe bring in the best candidates to meet our existing team, and we make hiring decisions together. Most of our engineering team has the same job title, "Senior Engineer", and we tend to operate by consensus and behave as peers among equals. One of our founders is an engineer, and has focused on making EDITD the place he wished he always worked.We use the best tools, and offer the best environment we can. We've got huge scope to innovate and we always welcome fresh perspective. You'll be able to make a bigger impact, and learn more in this job than any you've had before, we guarantee it.The jobEDITD is looking for a data scientist to help set up our data science team.The data team is responsible for understanding how the apparel market is working, and help understand how our customers can use data to help them make important and risky financial decisions on what products to buy, how to price them, and when to discount.The team is also responsible for augmenting our data using machine learning and data mining techniques to categorise products, understand trends, project future behaviours and correlate information across datasets.You'll get the opportunity to choose your tooling, explore the problem space, understand what we're trying to achieve with our product managers and customers, and take a concept right through to a delivered product.This is a senior role, and has the option to (but not the requirement to) lead the data team.You will:have an ability to find insights from huge volumes of data, and generalise the models to do so.be experienced productising machine learning techniques in a reliable, robust environment.be a great communicator - you can explain a pearson coefficient to a manager, a software engineer, or a retail buyer.understand how to visualise data, present and communicate the findings from your analysis.work closely with the product and data teams, to help them express and communicate data.be an opinion leader within the engineering team, and we'll look to you to set the tone for how we handle data.

Requirements:
Essential:Concise verbal and written articulation of complex ideas.Knowledge of one or more of the following: classification techniques in machine learning, data mining, applied statistics, data visualisation, computer vision.A thirst for knowledge.Extensive programming experience.A collaborative, friendly approach, good manners, a constructive viewpoint, and a team player.Experience with large-scale analysis components such as Hadoop and pig, or column stores such as Redshift or Cassandra, or commercial OLAP tools.Bonus points:Experience with forecasting Information architecture experience.Data mining or machine learning competition (such as the Netflix prize, or Kaggle) experience.An expert in using tools such as R or Pandas, Numpy and Scipy.

Benefits: